mahabharahta/my_awesome_wnut_model

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0944
  • Validation Loss: 0.2261
  • Train Precision: 0.6429
  • Train Recall: 0.4737
  • Train F1: 0.5455
  • Train Accuracy: 0.9509
  • Epoch: 2

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 636, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Precision Train Recall Train F1 Train Accuracy Epoch
0.2774 0.2932 0.5372 0.2416 0.3333 0.9359 0
0.1424 0.2377 0.6149 0.4258 0.5032 0.9481 1
0.0944 0.2261 0.6429 0.4737 0.5455 0.9509 2

Framework versions

  • Transformers 4.44.2
  • TensorFlow 2.17.0
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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